Computer Tomography (CT) X-ray data is computationally compiled from absorption data of X-rays that pass through an object and reconstructed into an image. An image with low attenuation regions such as soft biologic tissue can contain artifacts generated by high attenuation objects. Artifacts degrade the quality of the CT image, obstruct identification and/or diagnosis and should be removed to give an accurate image. Artifact reduction is sometimes accomplished through reprojection and reconstruction of the image using a number of mathematical systems.
Some systems make computations on all scan data, reconstructing the image pixel-by-pixel. Typically, these methods require many iterative steps and are computationally complex and slow. Such a method is disclosed in U.S. Pat. No. 5,243,664 to Tuy.
Other methods are less computationally complex, but discard high attenuation objects along with the artifacts so they may be missing important high attenuation parts of the image. An example of this system is seen in U.S. Pat. No. 4,590,558 to Glover et al.
U.S. Pat. No, 4,709,333 to Crawford, describes a similar method where two high attenuation objects shadow each and both objects and their artifacts are removed from the image.
Other systems reduce artifacts using interpolation of the two-dimensional Fourier transform of the image and reprojection, as seen in U.S. Pat. No. 4,616,318 to Crawford.
U.S. Pat. No. 4,626,991 to Crawford uses multiple reprojections sent to a backprojector and then combines the data with the original projections to correct for “polychromatic aberrations” in a non-cone beam CT X-ray scanner.
U.S. Pat. No. 4,714,997 to Crawford describes a method for shortening image processing time by reducing the reprojection data used in reconstructing the image.
U.S. Pat. No. 6,094,467, to Gayer et al. describes a method that reduces the complexity of the algorithmic functions by determining the extents of the high attenuation objects.